Abstract
Optimized system configuration is the key point to improve performance of earth observation satellite system(EOSS).However,its performance can not be calculated analytically.To solve the problem of EOSS optimization,we propose a simulation based optimization method,in which Kriging surrogate model is built to approximate simulation data.Points with optimized values or maximal expected improvement are selected to update our surrogate model.And a measure named objective improvement versus distance is defined to filtrate the selected points.To get the optimized solution of the surrogate model,we construct an improved generalized pattern search algorithm.In the search step,genetic algorithm and sequential quadratic programming are used to find potential update points.In the poll step,dynamic incompletion poll is carried out to find points with greater value.Finally,through a series of test cases and contrastive experiments,the results prove that our method is e?ective.
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